Staff Data Scientist, Algorithm, Growth

About Airwallex

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.

We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.

We're co-headquartered in San Francisco and Singapore, with more than 2,700 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.

How you'll make impact

You’ll shape the next phase of Airwallex’s growth by building data science systems that improve how we acquire, activate, engage, retain, and expand customers globally.

• Design, deploy, and iterate on predictive models, personalization and recommendation systems, LLM-powered applications, incentive optimization frameworks, and causal inference models that drive measurable business outcomes.

• Partner with Growth, Marketing, Product, Sales, Engineering, and other cross-functional teams to turn data and AI into clear recommendations, stronger investment decisions, and effective go-to-market strategies.

• Measure the causal impact of marketing and growth initiatives, identify what’s working, and translate those findings into action.

• Raise the technical bar for the data science team through hands-on leadership, mentorship, and a clear vision for longer-term direction.

You’ll be based in San Francisco and work from the office three days a week.

What we're looking for

Essentials

• 7+ years of industry experience and an advanced degree, such as a PhD or MS, in a quantitative field such as Statistics, Engineering, the Sciences, Computer Science, or Economics.

• Expert knowledge of machine learning and statistical modelling for data-driven growth strategy.

• Hands-on experience building, deploying, and maintaining machine learning models in production-grade systems, including cloud-based services and real-time or batch pipelines.

• Strong experience with data querying languages such as SQL and scripting languages such as Python.

• Experience applying machine learning and statistical models to measure the causal impact of marketing or growth initiatives.